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Diploma in Financial and Data Analytics
Duration - 6 Month, 8-10 hours/week
Course fee: - INR 63000
This course is recognized by the National Skill Development Corporation, a PPP under the Ministry of Skill Development and Entrepreneurship of the Government of India. You will receive a certificate cobranded by NSDC and Skill India on successful completion.
Syllabus
Finance and Accounting Foundations 
Financial Principles and Concepts
Fundamental financial concepts such as profit, loss, investments, and assets. Understand the significance of time in financial transactions and how risk influences investment returns.
Accounting Fundamentals
Essentials of accounting, covering topics like maintaining accurate financial records, understanding accounting equations, and recording transactions to maintain financial transparency.
Financial Statement Analysis
Proficiency in analyzing financial statements including income statements, balance sheets, and cash flow statements. Learn to interpret these statements to evaluate a company's financial performance and stability.
Budgeting and Forecasting
Master the art of budget creation and financial forecasting. Explore techniques for creating budgets, predicting future financial scenarios, and conducting scenario analysis to prepare for various bus
Practical Skills: Practice analyzing real financial reports and creating forecasts using tools like Excel.
Sensitivity Analysis
Introduction to sensitivity analysis: Definition, importance, and scope
Key concepts: Variable sensitivity, scenario analysis, and simulation
Implementing Sensitivity Analysis in Excel: Building models, data tables, scenario manager, and using Excel's built-in functions for sensitivity analysis
Case Studies: Real-world examples of sensitivity analysis in investment appraisal, capital budgeting, and portfolio management
Important Statistics for Data Analysis in Finance & Other Business Departments
Descriptive Statistics
Measures of central tendency,
variability
data distributions.
Inferential Statistics
Techniques for making predictions and inferences
Sampling, estimation, and hypothesis testing
Probability Distributions
Normal, binomial, and Poisson distributions, and their applications in data analysis.
Regression Analysis
Practical Skills: Implement statistical tests and regression models using programming languages like Python or R.
Practical Skills: Implement statistical tests and regression models using programming languages like Python or R.
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Data Visualization and Business Intelligence Tools & Techniques
Data Visualization Principles
Principles of effective data visualization
Visualization types
How to use common visualisation tools in Excel & PPT
Tableau Dashboards and Stories
Power BI Reports and Visualization
Business Intelligence Concepts
Understand concepts behind business intelligence systems, including BI architecture, data warehousing, and OLAP cubes.
Practical Assignment: Develop interactive dashboards using Tableau and Power BI.
Investments and Portfolio Management
Investment Theories and Strategies
Theories and strategies for making investment decisions. Understand modern portfolio theory, the capital asset pricing model, and various investment styles to effectively manage investment portfolios.
Portfolio Analysis and Optimization
Analyze investment portfolios, calculate returns, and assess risks to optimize portfolio performance. Discover strategies for diversification and risk management to achieve investment objectives.
Risk Management
Different types of investment risks and strategies for mitigating them. Explore hedging techniques and risk management strategies to protect investments from market volatility.
Financial Markets and Instruments
Overview of financial markets and the various financial instruments traded within them, including equities, debt, and derivatives.
Practical Skills: Practice building optimal investment portfolios and assessing risks using tools like Excel and Python.
Data Mining and Machine Learning
Data Preprocessing and Cleaning
Handling missing values,
Outliers
feature engineering
Exploratory Data Analysis
Supervised Learning algorithms
Supervised learning algorithms for regression and classification tasks, including linear and tree-based models.
Unsupervised Learning techniques - Model Evaluation and Optimization, Cross-validation, Hyperparameter tuning.
Practical Skills: Wrangle data and build predictive models using Python or R libraries.
Storytelling with Data
What
How to Data Storytelling and Presentations
Learn to effectively communicate your findings through compelling data presentations.
Professional Portfolio Development
Practical Skills: Collaborate on a group capstone project and present your portfolio to potential employers.
Career Prospects:
Financial analyst, investment analyst, data analyst, business intelligence developer, data scientist, portfolio manager, and other finance/analytics roles.
Course Plan
Standard
RS. 63000
incl. of all charges
Printed study material (by courier)
2 practical exercises/ Drafting exercises per week (24 weeks)
6 writing assignments
1-2 online live class/week
Get digital access to entire study material
Access on LMS, Android & iOS app
Instructor feedback on assignments
Doubt clearing on WhatsApp, LMS & classes
Instructor led course with online live classes
Online exams (give exams as per your convenience on given time slots)
Certificate (by courier)
CV enhancement
Coaching for professional networking
Internship & job support
Interview preparation support
Networking with students & alumni
Content access for 3 years
Doubt clearing within 24 hours
Top performers are recommended for jobs and client opportunities
